Multicenter Validation of an <scp>MMSE</scp>‐Mo<scp>CA</scp> Conversion Table

Bergeron, David; Flynn, Kelsey; Verret, Louis; Poulin, Stéphane; Bouchard, Rémi W.; Bocti, Christian; Fülöp, Tamás; Lacombe, Guy; Gauthier, Serge; Nasreddine, Ziad; Laforce, Robert

doi:10.1111/jgs.14779

Cited by 112 publications

(136 citation statements)

References 32 publications

Supporting

Mentioning

112

Contrasting

Unclassified

Order By: Relevance

“…In daily clinical practice, converting scores directly with the table derived from the log-linear smoothing method appears to be more convenient than using the regression equations, but the latter method can be used for more accurate conversion in settings where clinical calculators are available. As previously reported, 11 our data also revealed a prominent floor effect in the MoCA and the MoCA 5-min as score approached zero on the MoCA and the MoCA 5-min when MMSE score fell below 7 and 9, respectively ( Table 3). Given that the MoCA and the MoCA 5-min are designed for the detection of subtle decline at the higher end of the cognitive spectrum, these tests may not be suitable for measuring cognitive functions in patients with severe impairment, such as those with MMSE scores of 10 or below.…”

Section: Ies Accordingly Conversion Equations Based On Poisson Regrsupporting

confidence: 90%

“…Score conversion between the 2 tests has been reported previously in samples involving healthy controls, patients with MCI, Alzheimer's and Parkinson's Disease, and cognitive impairment clinic samples ( Table 1). [9][10][11][12][13][14] However, such investigation has not been performed in patients with stroke or TIA. A major limitation in most score conversion studies is that in these studies MoCA scores were back equated to MMSE rather than vice versa.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Converting MMSE to MoCA and MoCA 5‐minute protocol in an educationally heterogeneous sample with stroke or transient ischemic attack

Wong

Black

Yiu

et al. 2018

Int J Geriat Psychiatry

View full text Add to dashboard Cite

show abstract

Section: Ies Accordingly Conversion Equations Based On Poisson Regrsupporting

confidence: 90%

mentioning

confidence: 99%

Converting MMSE to MoCA and MoCA 5‐minute protocol in an educationally heterogeneous sample with stroke or transient ischemic attack

Wong

Black

Yiu

et al. 2018

Int J Geriat Psychiatry

View full text Add to dashboard Cite

show abstract

“…Patients and controls underwent a standardized medical and neurological evaluation including: neurological examination by an experienced movement disorders specialist, assessment of rapid eye movement (REM) sleep behavior disorder (RBD) in a personal medical interview with questioning analogous to the REM Sleep Behavior Disorder Single-Question Screen, 6 7 Hence, a valid MoCA score was available for each subject. All clinical assessments were done before genetic analysis was performed.…”

Section: Clinical Assessmentmentioning

confidence: 99%

Dementia with lewy bodies: GBA1 mutations are associated with cerebrospinal fluid alpha‐synuclein profile

et al. 2019

View full text Add to dashboard Cite

Background Patients with dementia with Lewy bodies reveal a variable pathology including alpha‐synuclein, amyloid‐beta, and Tau. Mutations in GBA1 are specifically associated with synucleinopathies. PD patients with GBA1 mutations show reduced CSF levels of total alpha‐synuclein. Objective Whether GBA1 mutations are associated with a CSF alpha‐synuclein profile in dementia with Lewy bodies. Methods Screening of the GBA1 gene and single‐nucleotide polymorphisms in SNCA rs356220, APOE rs429358, and MAPT rs1052587 as well as CSF levels of total alpha‐synuclein, amyloid‐beta1‐42, total‐Tau, phospho‐Tau, and neurofilament light chain were assessed in 100 dementia with Lewy bodies and 39 controls cross‐sectionally. Results Severity of GBA1 mutations was associated with a younger age at onset and higher prevalence of rapid eye movement sleep behavior disorder. CSF levels of total alpha‐synuclein were lowest in DLBGBA_pathogenic compared to DLBGBA_mild and DLBGBA_wildtype. Conclusion Similar to PD, pathogenic GBA1 mutations seem to be associated with CSF alpha‐synuclein profiles in dementia with Lewy bodies. That might be useful for patient stratification for specific alpha‐synuclein–lowering compounds. © 2019 International Parkinson and Movement Disorder Society

show abstract

“…We divided the MoCA scores into three groups (MoCA score of 0~10, 11~17 and 18~30 points) [15][16][17].…”

Section: Discussionmentioning

confidence: 99%

Low Bone Mineral Density Could Predict Cognitive Impairment during the Acute and Recovery Phases of Ischemic Stroke

Lee

Jang

Kim

et al. 2020

Preprint

View full text Add to dashboard Cite

KEYWORDS osteoporosis, bone mineral density, cognitive impairment, white matter disease, ischemic stroke 2 Abstract Background Little is known about the effect of osteoporosis at the acute and recovery phase of stroke on cognitive function. We evaluated the effect of osteoporosis on cognitive function in patients with ischemic stroke aged >50 years. Methods We retrospectively examined consecutive patients with acute stroke hospitalized between 2016 and 2018. Osteoporosis was defined as a T score of <-2.5 for the femoral neck or lumbar spine bone mineral density. The primary outcome was cognitive impairment measured by the Korean Mini-Mental State Examination in the acute phase and recovery phase of ischemic stroke. The association between osteoporosis and the severity of cognitive impairment was investigated using a multivariate analysis. Results Of the 260 included subjects (107 men and 153 women), 70 (26.9%) had osteoporosis. Cognitive impairment was more severe in the osteoporosis group than in the non-osteoporosis group (30.5% versus 47.1%, p=0.001). After recovery phase of stroke, the proportion of patients with cognitive impairment remained higher in the osteoporosis group. The multivariate analysis revealed a correlation between a low femoral neck bone mineral density and severe cognitive impairment in the acute and recovery phases of stroke (adjusted odds ratio [OR] 3.66, 95% confidence interval [CI] 1.05-12.79 in the acute phase and adjusted OR 11.17, 95% CI 1.12-110.98 in the recovery phase), whereas lumbar spine osteoporosis was not associated with cognitive impairment. Conclusions Low bone mineral density is associated with poor cognitive function in patients with acute stroke. Early bone mineral density assessments during acute stroke, particularly at the femoral neck, may be a useful marker of cognitive function.

show abstract

Multicenter Validation of an MMSE‐MoCA Conversion Table

Abstract: In this study, we validated a conversion table between MMSE and MoCA using a large multicenter sample. Our results suggest caution in interpreting the tables in heterogeneous clinical populations, as the MMSE-MoCA relationship may be different across dementia subtypes.

Cited by 112 publications

References 32 publications

Converting MMSE to MoCA and MoCA 5‐minute protocol in an educationally heterogeneous sample with stroke or transient ischemic attack

Converting MMSE to MoCA and MoCA 5‐minute protocol in an educationally heterogeneous sample with stroke or transient ischemic attack

Dementia with lewy bodies: GBA1 mutations are associated with cerebrospinal fluid alpha‐synuclein profile

Low Bone Mineral Density Could Predict Cognitive Impairment during the Acute and Recovery Phases of Ischemic Stroke

Contact Info

Product

Resources

About